AI Compute Capacity
ANTARES owns and operates the GPU infrastructure, providing managed compute capacity under customer-specific service terms.
ANTARES builds and operates modular GPU infrastructure for enterprise AI inference.
ANTARES owns and operates the GPU infrastructure, providing managed compute capacity under customer-specific service terms.
Customers bring their own GPU hardware. ANTARES provides the facility, power, cooling and connectivity required to operate it.
Production AI depends on available power, cooling, GPUs, network connectivity and an operating environment that meets uptime, security and data-location requirements.
For enterprises, compute capacity is not interchangeable. The relevant questions are where it is located, when it can be commissioned, which hardware it supports and whether it can expand with demand. ANTARES addresses that layer directly by integrating the physical systems required to run AI workloads continuously.
Fast-moving, iterating weekly
Slow-moving, the foundation
Production inference serves live, variable demand. Capacity must be planned around response time, availability, data location and operating cost, not only GPU performance.
ANTARES focuses on sustained inference environments designed for continuous service and measured expansion.
ANTARES integrates enclosure, protected power, liquid cooling, networking and GPU systems into a modular deployment. At power-secured, permit-ready sites, the target is 12 to 18 months to operation; conventional greenfield programs can require five to seven years when power access and site development are included.
ANTARES evaluates locations across European markets according to customer proximity, available power, connectivity, site readiness and jurisdiction. Capacity is not tied to one fixed mega-campus.
Sovereign infrastructure gives customers defined choices over where systems operate, who can access them and which operating model applies. Network design, identity controls, application architecture and contractual responsibilities determine how those choices work in practice.
For production inference, regional placement can shorten network paths to users and support defined workload-location requirements. Separate locations limit shared physical failure, while modular capacity can be added where power, permits and demand are available. Continuity across sites still requires explicit replication, routing and recovery design.
ANTARES coordinates site readiness, system design, equipment integration and the operating model. Suppliers are qualified for each project against compatibility, availability, support and lifecycle requirements.
Power, permits, connectivity and site constraints are validated before the equipment configuration is fixed.
Site preparation and factory fabrication can proceed in parallel. Timing still depends on power, permits, equipment supply and commissioning scope.
Electrical, thermal, compute and network architecture are specified together for the site and intended workload.
Telemetry, access control, maintenance, spares and incident response are defined before commissioning.
The appropriate structure depends on the project, its assets, customer arrangements, financing requirements and participating parties. The examples below explain the available concepts at a high level.
Direct title to identified GPU hardware, hosted and operated under contract by ANTARES. Returns depend on utilization, pricing, operating costs and the equipment's useful life.
A project-level debt instrument. Coupon, maturity, security package, covenants and any conversion rights are defined for each issuance.
Equity participation in a defined infrastructure project. Outcomes depend on customer contracts, utilization, operating costs, financing and residual asset value.
This website provides an overview of ANTARES AI infrastructure activities and a starting point for customer, site, financing and media discussions. Detailed information is developed for each specific project.
Relevant inquiries may come from organisations seeking AI capacity, owners of GPU hardware, site and power providers, technology suppliers, financing parties and journalists.
Potentially. Compatibility depends on the hardware format, power density, cooling requirements, networking, support status and intended workload. These factors are reviewed before a configuration is proposed.
No single location is assumed for every project. The appropriate site is considered in relation to customer needs, technical requirements, power availability and the required jurisdiction.
Discussions may concern AI compute capacity, GPU colocation, direct GPU ownership, project equity or project debt. Not every route will be appropriate or available for every project.
An inquiry can begin with an early site or capacity concept, an identified customer requirement, existing GPU hardware or a more developed infrastructure project. The next steps depend on what has already been established.
ANTARES reviews the information, identifies the relevant internal contact and determines whether further technical, commercial or project documentation is needed before arranging the next discussion.
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